THE ASSYMMETRIC RELATIONSHIP BETWEEN CUSTOMER SATISFACTION, DISSATISFACTION, LOYALTY AND FINANCIAL PERFORMANCE IN B2B COMPANIES

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1 THE ASSYMMETRIC RELATIONSHIP BETWEEN CUSTOMER SATISFACTION, DISSATISFACTION, LOYALTY AND FINANCIAL PERFORMANCE IN B2B COMPANIES By Dr Rhian Silvestro, Associate Professor and Head of Operations Management Group, Warwick Business School, University of Warwick, Coventry, CV4 7AL and Tse How Low (Don), Manager, Tech Mahindra, Singapore ABSTRACT It has been argued and is often assumed that the financial performance of service organisations relies on the generation of high levels of customer satisfaction and loyalty (see for example, Heskett et al, 1994, Rucci et al, 1998, Reichheld and Markey, 2000, Vander merwe, 2000, Fredericks, 2001, Reichheld, 2004). However a number of contributions to the services marketing and service operations literatures over the past decade have called this into question and empirical studies have begun to demonstrate service contexts in which customer satisfaction and loyalty do not always correlate positively with financial performance (Wiley, 1991, Loveman, 1998, Silvestro and Cross, 2000, Pritchard and Silvestro, 2005, Kamakura, 2002). Most of these empirical studies have been based on business to consumer contexts, and on latitudinal rather than longitudinal data (notable exceptions here being Bernhardt and Donthu, 2000 and van der Wiele et al, 2002). This paper explores the relationship between customer satisfaction, loyalty and financial performance in the context of the telecommunications industry. A large European telecom company was studied, comprising four different businesses, one of which serves consumers, the other three being business to business companies; and a longitudinal analysis was conducted of correlations between financial performance and customer satisfaction, customer dissatisfaction, customers stated intention to repurchase, and their stated willingness to recommend the service. The results indicated, in line with the literature, that dissatisfaction was negatively correlated with revenue in all four businesses; whilst customer satisfaction was strongly correlated with revenue in only one of the companies, a B2B service. The relationship between financial performance and loyalty was less conclusive, and sometimes confusing. Advocacy was found to be positively correlated with revenue in two of the companies. However, there was little evidence of a significant relationship between customer retention and revenue; indeed, counter-intuitively, the B2C company demonstrated a negative correlation between customer retention and revenue.

2 This study indicates that in contexts where customer satisfaction does not drive revenues, there may nevertheless be a link between customer dissatisfaction and financial performance; and highlights the efficacy of measuring dissatisfaction as well as mean satisfaction levels. The results also endorse the growing academic interest in non-linear and asymmetric performance relationships (Mittal et al, 1998, Anderson and Mittal 2000) and point to the fact that dissatisfaction may be more closely related to financial performance than satisfaction, particularly when maintenance rather than enhancing attributes are most valued by the customer. The relationship between customer loyalty and revenues was less conclusive, but the explanation for this appeared to lie in the nature of the competitive arena rather than in differences based on the B2C and B2B typology. Further research is required in order to explore differences in the performance relationships between B2C and B2B companies.

3 INTRODUCTION It has been argued and is often assumed that the financial performance of service organisations relies on the generation of high levels of customer satisfaction and loyalty (see for example, Heskett et al, 1994, Rucci et al, 1998, Reichheld and Markey, 2000, Vandermerwe, 2000, Fredericks, 2001, Reichheld, 2004). However a number of contributions to the services marketing and service operations literatures over the past decade have called this into question and empirical studies have begun to demonstrate service contexts in which customer satisfaction and loyalty do not always correlate positively with financial performance (Wiley, 1991, Loveman, 1998, Silvestro and Cross, 2000, Kamakura, 2002, Pritchard and Silvestro, 2005). Most of these empirical studies have been based on business to consumer (B2C) contexts, and on latitudinal rather than longitudinal data. A notable exception here is the work of Bernhardt et al, 2000, whose empirical study showed that in a context where there at first appeared to be no significant relationship between customer satisfaction and performance, the analysis of time-series data revealed a significant positive relationship between changes in customer satisfaction and changes in performance. They demonstrated that latitudinal analysis of snapshots of performance fail to take into account time lags in performance. Longitudinal studies on the other hand can reveal performance relationships that might otherwise not be demonstrable (Van der Wiele et al, 2002) This paper raises the question whether the performance linkages between customer satisfaction, loyalty and financial performance might be expected to be different in business to business (B2B) service contexts. These performance relationships are studied in the context of the telecommunications industry, using longitudinal data over a two year period in order to see what can be concluded about the drivers of financial performance in B2B services. A large European telecom company was studied, comprising four different businesses, one of which serves consumers, the other three being B2B services. This facilitated some comparison of the performance relationships in B2B and B2C contexts within the same industry, even though the nature and mix of the services offered by the different companies varied. The companies can be briefly profiled as follows: Consumer Services: The company offered a wide range of telephone and internet services to a high volume customer base in a competitive market in which it formerly occupied a monopoly position. In the face of growing competition its revenues overall were in decline, although it was experiencing high growth in its new wave technology markets. Small Business Services: The company provided the same range of telecommunications services to well over a million small and medium sized enterprises. The service offerings are more tailored to individual customer needs

4 than the standardised offerings provided to the higher volume Consumer Services. Corporate Business Services: The company served large corporations internationally, with a presence in 170 countries, and accounted for over a third of the telecommunications company s total revenue. The method of attracting and retaining customers was very different from the other businesses: new business accounts required relationship management and usually winning the bid was determined by many factors other than price, product features or even service quality: they valued the consultancy firm-client relationship and this had a major impact on the purchasing decision. Wholesale Services: The company provided network services and solutions to communications companies, many of whom were competitors of the other companies. Wholesale Services was a low volume, high value business, where 70% of the revenues were accounted for by only 12 clients. Thus the loss of a single client could dramatically effect the company s business. Wholesale Services was formerly a monopoly and the company still dominated the telecommunication wholesale market which was consequently heavily regulated. The company had been measuring the correlation between customer satisfaction and revenue over many years and the management philosophy of the organisation was based on the commonly held view that customer satisfaction drives revenue growth. However the performance data over the years had in fact lent little support for this assumption. It was therefore decided that other performance linkages should be explored in order to better understand the drivers of financial growth, and the company introduced two measures of customer loyalty across the businesses: customer retention and advocacy. Management also decided to explore the relationship between customer dissatisfaction and financial performance. Thus as well as measuring mean customer satisfaction, it also began to measure the percentage of dissatisfied customers to see whether there might be a negative link between customer dissatisfaction and revenue. For if it could be demonstrated that revenues decline when dissatisfaction rises, then this would in effect confirm a relationship between satisfaction and revenue which was not being made manifest using the measure of average satisfaction levels. METHODOLOGY A longitudinal analysis was conducted of correlations spanning a two year period, , using the following measures of satisfaction, loyalty and financial performance: Customer satisfaction: mean satisfaction levels, measured on a 1-7 scale semantically defined as follows: Extremely, Very, Fairly satisfied, Neither satisfied nor dissatisfied, Fairly, Very and Extremely dissatisfied. Customer dissatisfaction: percentage of Fairly, Very and Extremely dissatisfied customers, based on the same data and measurement scale as the satisfaction measure.

5 Customer retention: customers stated likelihood of repurchase, measured on a 1-7 scale; mean levels calculated. Customer advocacy: customers stated likelihood to recommend the company to friends, measured on a 1-7 scale. Advocacy was calculated on the basis of the percentage of customers stating that they were Extremely Likely to Recommend or Very Likely to Recommend ; it was assumed that those who were only fairly likely to recommend could not be considered strong advocates of the service. Revenue: quarterly revenue data for each business. The pairs of variables were subjected to correlation analysis of the quarterly data using Pearson s correlation coefficient. The following null hypotheses were tested and were rejected only if the correlation was significant at a minimum 95% confidence level: H1: There is no performance relationship between customer satisfaction and revenue H2: There is no performance relationship between customer dissatisfaction and revenue H3: There is no performance relationship between customer retention and revenue H4: There is no performance relationship between customer advocacy and revenue H5: There is no performance relationship between customer satisfaction and loyalty The aims of the research also included exploring any similarities or differences between the performance relationships found in B2C and B2B businesses. Following on from the correlation analysis interviews with twelve senior managers across the four businesses were conducted in order to see whether the results accorded with their intuition and expectations, and to invite their explanations of the findings. FINDINGS The findings in each company are now discussed in turn; and explanations based on the interviews with management are provided as appropriate. We begin with the B2B companies.

6 Small Business Services Figure 1: Small Business Services In the Small Business Services there was a positive correlation between revenue and satisfaction and a negative correlation with dissatisfaction, suggesting a direct relationship between satisfaction and revenues which is very much in line with the service quality literature: as satisfaction decreases and dissatisfaction increases, revenues decline. Interviews with managers revealed that, during this time, a new technology had been introduced and teething problems had been experienced by customers, which explained the drop in satisfaction levels. However, there appeared to be no relationship between either intention to repurchase or willingness to recommend and revenues.

7 Corporate Business Services Figure 2: Corporate Business Service In the Corporate Business Services there was a strong negative correlation between dissatisfaction and revenue but no other performance relationships with revenue were confirmed. This is surprising in that one might expect revenues to be closely linked to customer loyalty in a low volume B2B company with high value accounts. There was, however a positive correlation between the two loyalty measures, retention and advocacy. Intuitively this is what one would expect: that customers willingness to recommend the company would increase with their stated repurchase intentions. The lack of correlation between both the loyalty measures and revenues, may be due to the fact that customers perceived few market alternatives and therefore their willingness to stay with or recommend the company did not drive revenues. Even when dissatisfaction levels are high, this may not translate into a willingness to switch due to the company s strong market position and the dearth of competitive alternatives. Interviews with management confirmed this explanation but further revealed that the buying decisions made by the client companies are determined by a group of senior management, whose purchase decisions often hinge on factors unrelated to product/service quality, like plans for long term partnerships. Furthermore, the services offered within this context are particularly dissatisfaction-prone : indeed, operations reliability and failure recovery are critical to the clients businesses. The customer sensitive attributes here are therefore hygiene factors (Johnston 1995) or maintaining attributes (Anderson and Mittal, 2000), which create dissatisfaction when not delivered, but

8 do not significantly enhance perceptions of the service. In such contexts, dissatisfaction, rather than either satisfaction or loyalty, may be expected to be linked to financial performance. Wholesale Services Figure 3: Wholesale Services In Wholesale Services the only measure which correlated with revenue was advocacy. However there were links between the satisfaction and loyalty measures. Stated repurchase intentions and advocacy were correlated; and both these measures correlated with customer satisfaction. Interviews with managers highlighted the fact that the performance of this company was very susceptible to promotion and advocacy. Sharp, short term changes in revenues could result from media interventions and sudden changes in public perceptions, and so the link between advocacy and revenues had intuitive appeal. This suggests a chain of performance relationships linking customer satisfaction, intention to repurchase, willingness to recommend and revenues. Satisfaction, dissatisfaction and stated purchase intention did not correlate with revenues at the 95% significance level; however it might be noted that all correlations were close to the threshold and accorded with intuition, in that there were positive correlations between revenues and each of satisfaction and loyalty, and a negative correlation between revenue and dissatisfaction. Consumer Services Company

9 Figure 4: Consumer Services In the B2C company there was no correlation between satisfaction and revenue, but there was a strong negative correlation between dissatisfaction and revenue: as dissatisfaction increased, revenues declined. There were positive correlations between satisfaction, advocacy and revenues: performance against all three indicators had been in decline. The company s management confirmed that the performance relationships between dissatisfaction and revenue, and advocacy and revenue meshed with their experience. The absence of a link between satisfaction and revenue, but a negative correlation between dissatisfaction and revenue could be explained in terms of customers sensitivity to service failure, and the successful provision of telephony infrastructure being a hygiene factor (with limited potential to create customer satisfaction). They further explained that sales were heavily influenced by advocacy in this commoditised market: so, for example, promotion of a new technology could generate visibility of the service, resulting in advocacy which could directly affect sales even in the short term. However the relationship between loyalty and revenues was more confusing: there was a negative correlation between repurchase intention and revenue. Investigation into the raw data revealed that even though satisfaction and likelihood to recommend scores for the B2C company had declined over the years, the intention to repurchase scores had been steadily climbing. Thus customers intention to repurchase was not apparently affected by the drop in satisfaction (quite the reverse); but the likelihood to recommend was affected. Perhaps intention to repurchase did not decrease with dissatisfaction because of a perceived lack of alternative suppliers: the company was formerly in a

10 monopoly position and remained a dominant player in the market. It may be that purchase intention was therefore more closely linked with availability of alternatives than the service performance of the company. Customers reluctance to switch may be a classic exhibition of latent loyalty (Ping, 1994; Jones and Sasser, 1995), whereby customers do not switch despite high levels of dissatisfaction. Cross-business Analysis The correlation analysis resulted in the following findings with respect to each of the hypotheses. H1: There is no performance relationship between customer satisfaction and revenue Only Small Business Services showed a significant positive correlation, whereby customer satisfaction dropped in line with revenues. H2: There is no performance relationship between customer dissatisfaction and revenue Significant negative correlations were found in Consumer, Small Business and Corporate Services. In Wholesale Services the correlation was also negative, but just fell short of the 95% significance threshold. This is, therefore, the hypothesis that came closest to being disconfirmed. H3: There is no performance relationship between customer retention and revenue There were no significant positive correlations in any of the companies. However, there was a negative correlation between retention and revenues in Consumer Services: as revenues declined, customers stated intention to repurchase increased. This is a counter-intuitive finding which flies in the face of the customer loyalty literature. H4: There is no performance relationship between customer advocacy and revenue Customers willingness to recommend the company was positively correlated with revenues in both Wholesale and Consumer Services. H5: There is no performance relationship between customer satisfaction and loyalty This was true of Small Business and Corporate Business Services. However, in Wholesale and Consumer Services there was a correlation between satisfaction and advocacy; and the correlation between satisfaction and retention was positive in Wholesale Services but negative in Consumer Services. None of the hypotheses were unequivocally confirmed or disconfirmed, but the hypothesised relationship between customer dissatisfaction and revenue (H2) came closest to being disconfirmed. In all four businesses (though the correlation was not significant in the Wholesale Services), dissatisfaction was negatively correlated with revenue at business levels. This is an interesting finding for the company. For many years the management had expected to be able to demonstrate a correlation between mean satisfaction levels and revenues, and had failed. This study suggests that

11 even if increased satisfaction does not drive financial performance, high levels of dissatisfaction may well have a deleterious effect on growth. Thus delivering higher service levels and satisfying customers may not lead to enhanced financial returns, but dropping service levels may well reduce financial returns. It is important that a company which is in this position does not promote management rhetoric which conflicts with this business reality. The message for employees in such a context must be that it is important to maintain service levels because reducing them will have a negative impact on financial performance, rather than arguing that improving service levels will necessarily drive growth. If employees perceive a mismatch between the business reality and the management rhetoric, scepticism and cynicism is likely to follow. This points to the value of this type of correlation analysis because it enables managers to provide support for the performance relationships which form the basis of the company s business model, whilst challenging what might be longstanding misconceptions about the drivers of financial performance. When the data do not fit the facts, managers can then explore the reasons which might explain the absence of an expected link or a counter-intuitive correlation. This facilitates organisational learning and can inform the development of business strategies. This study also points to the relevance and usefulness of measuring the percentage of dissatisfied customers, rather than simply focusing on mean satisfaction levels. It has been argued by Mittal et al, 1998 and Anderson and Mittal, 2000, that in some contexts there may be an asymmetry in performance relationships, whereby, for example, financial performance may be driven by high performance of a variable, but is unaffected by low performance, or vice versa. They argue that maintenance attributes (sometimes called hygiene factors, Johnston, 1995) may create dissatisfaction when not delivered, but have little impact on satisfaction; whilst conversely, enhancing attributes may create high levels of satisfaction when delivered effectively, but their absence may have little impact on dissatisfaction. This is clearly relevant in the telecommunications industry, and to all four of the businesses in this study. Customers of all four of the businesses are highly sensitive to service failures; indeed it is often only in the context of a service failure that customers make contact with the service and that the business becomes visible to the customers. The consistent provision of error free services is something the customers expect, but is rarely considered to be a source of customer delight. Thus customer dissatisfaction may be translated into a decline in revenues over time, whilst customer satisfaction will not itself necessarily drive growth. The point here is analogous to a point made in the customer loyalty literature: where the relationship between customer satisfaction and loyalty is non-linear (such that only highly satisfied customers remain loyal), the proportion of highly satisfied customers can be a more significant performance measure (if a company is pursuing a loyalty strategy) than mean satisfaction levels (Jones and

12 Sasser, 1995). Similarly, if customers are highly sensitised to failure and are relatively insensitive to service quality enhancements, then the proportion of dissatisfied customers may be more important and revealing than mean satisfaction levels. This research study therefore concluded with some interesting findings about the relationship between customer satisfaction, dissatisfaction and revenue growth. The relationship between customer loyalty and revenue growth, however, proved to be less conclusive. There was evidence of a positive correlation between customer advocacy (willingness to recommend) and revenues in both Wholesale and Consumer services, where both aspects of performance were in decline. Intention to repurchase only correlated with revenues in one company, Consumer Services, but the correlation was negative and counter-intuitive. This could only be explained in terms of the possible lack of competitive alternatives for customers to turn to in the event of their being dissatisfied with this company s services: as revenues declined, it may be that willingness to repurchase increased because of a perceived reduction in the availability of competitive offerings. This study reveals no clear account of the differences or similarities between the four companies on the basis of their B2C or B2B status. The competitive context appears to be of more relevance in explaining these research findings than the distinction between B2C and B2B organisations. The negative correlation between dissatisfaction and revenues was evident in both B2C and B2B contexts; whilst other performance relationships straddled the B2C/B2B divide. Overall the absence of a clear account of the relationship between customer loyalty and financial performance can also be explained in terms of the competitive environment in which this company operated, rather than in terms of the B2C/B2B distinction. Formerly a monopoly, this company remained a dominant player at group level, and it is likely that many customers might stay with the company despite their dissatisfaction with service levels; indeed such customers may be said to display latent rather than true loyalty, and may be hostages to the service organisation rather than truly loyal assets (Ping, 1994). CONCLUSIONS This study has highlighted that in contexts where customer satisfaction does not drive revenues, there may nevertheless be a link between customer dissatisfaction and financial performance. The study highlights the relevance and efficacy of measuring dissatisfaction as well as mean satisfaction levels. The results also endorse the growing academic interest in non-linear and asymmetric performance relationships (Mittal et al, 1998, Anderson and Mittal 2000) and point to the fact that dissatisfaction may be more closely related to financial performance than satisfaction, particularly when maintenance rather than enhancing attributes are most valued by the customer.

13 The relationship between customer loyalty and revenues was less conclusive. The explanation for this appeared to lie in the nature of the competitive arena rather than differences based on the B2C and B2B typology. Further research is required in order to explore differences in the performance relationships between B2C and B2B companies. This research study further points to the value of analysing longitudinal data. The literature to date has presented mainly latitudinal empirical studies of multisite organisations where correlations can be measured at unit level at particular snapshots in time. Clearly performance relationships also need to be explored longitudinally in order to better understand the drivers of financial performance and the contingent variables which impact them. Finally, on a more pragmatic level, the study highlights the importance of managers developing a robust and sensitive understanding of performance relationships in their own organisations, rather than making managerial assumptions about those relationships which may turn out to be unsubstantiated. The prevalent management rhetoric on relationships between satisfaction, loyalty and financial performance should always be challenged and tested.

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